Triple
T4208205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Licensed to Ill |
E93831
|
entity |
| Predicate | hasInfluenceOnGenre |
P22766
|
FINISHED |
| Object | rap rock |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: rap rock | Statement: [Licensed to Ill, hasInfluenceOnGenre, rap rock]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInfluenceOnGenre Context triple: [Licensed to Ill, hasInfluenceOnGenre, rap rock]
-
A.
hasGenreInfluenceOn
chosen
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
B.
influencedByGenre
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
-
C.
hasMainGenre
Indicates that an entity’s primary or most characteristic genre is the specified genre.
-
D.
hasNotableGenre
Indicates that an entity is significantly associated with a particular genre, such that the genre is especially characteristic or noteworthy for that entity.
-
E.
hasGenreStrength
Indicates that something possesses a particular intensity or degree of emphasis associated with a specific genre.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:03 p.m.